Articles liés à Evidence-Based Statistics
Synopsis
Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches. The evidential approach is conceptually easier to grasp, and the calculations more straightforward to perform. This book explains how to express data in terms of the strength of statistical evidence for competing hypotheses.
The evidential approach is currently underused, despite its mathematical precision and statistical validity. Evidence-Based Statistics is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book.
While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician's "bag of tricks." In this book:
- It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion
- Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that's 'too good to be true', multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps)
- Equations are given for all analyses, and R statistical code provided for many of the analyses
- Sample size calculations for evidential probabilities of misleading and weak evidence are explained
- Useful techniques, like Matthews's critical prior interval, Goodman's Bayes factor, and Armitage's stopping rule are described
Recommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields, Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
PETER M.B. CAHUSAC, PHD, received his doctorate in neuropharmacology from the Medical School Bristol University in 1984. He completed post-doctoral studies at Oxford University where he obtained an MSc in Applied Statistics in 1992. He is a member of the British Pharmacological Society, and Fellow of the Physiological (UK) and the Royal Statistical Societies. He is currently Associate Professor in Biostatistics and Pharmacology at Alfaisal University in Riyadh, Saudi Arabia.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
- ÉditeurWiley
- Date d'édition2020
- ISBN 10 1119549809
- ISBN 13 9781119549802
- ReliureRelié
- Langueanglais
- Nombre de pages256
- Coordonnées du fabricantnon disponible
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An Introduction to Evidence Based Statistics
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ISBN 13 : 9781119549802
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Evidence-Based Statistics : An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice
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ISBN 13 : 9781119549802
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Evidenceâ"Based Statistics â" An Introduction to the Evidential Approach â" from Likelihood Principle to Statistical Practice
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ISBN 13 : 9781119549802
Neuf
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Evidence-Based Statistics : An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice
Edité par
Wiley, 2020
ISBN 10 : 1119549809
ISBN 13 : 9781119549802
Ancien ou d'occasion
Couverture rigide
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Evidence-Based Statistics : An Introduction to the Evidential Approach - From Likelihood Principle to Statistical Practice
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Buch. Etat : Neu. Neuware - Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice provides readers with a comprehensive and thorough guide to the evidential approach in statistics. The approach uses likelihood ratios, rather than the probabilities used by other statistical inference approaches. The evidential approach is conceptually easier to grasp, and the calculations more straightforward to perform. This book explains how to express data in terms of the strength of statistical evidence for competing hypotheses.The evidential approach is currently underused, despite its mathematical precision and statistical validity. Evidence-Based Statistics is an accessible and practical text filled with examples, illustrations and exercises. Additionally, the companion website complements and expands on the information contained in the book.While the evidential approach is unlikely to replace probability-based methods of statistical inference, it provides a useful addition to any statistician's 'bag of tricks.' In this book:\* It explains how to calculate statistical evidence for commonly used analyses, in a step-by-step fashion\* Analyses include: t tests, ANOVA (one-way, factorial, between- and within-participants, mixed), categorical analyses (binomial, Poisson, McNemar, rate ratio, odds ratio, data that's 'too good to be true', multi-way tables), correlation, regression and nonparametric analyses (one sample, related samples, independent samples, multiple independent samples, permutation and bootstraps)\* Equations are given for all analyses, and R statistical code provided for many of the analyses\* Sample size calculations for evidential probabilities of misleading and weak evidence are explained\* Useful techniques, like Matthews's critical prior interval, Goodman's Bayes factor, and Armitage's stopping rule are describedRecommended for undergraduate and graduate students in any field that relies heavily on statistical analysis, as well as active researchers and professionals in those fields, Evidence-Based Statistics: An Introduction to the Evidential Approach - from Likelihood Principle to Statistical Practice belongs on the bookshelf of anyone who wants to amplify and empower their approach to statistical analysis. N° de réf. du vendeur 9781119549802
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An Introduction to Evidence Based Statistics
Edité par
John Wiley & Sons, 2020
ISBN 10 : 1119549809
ISBN 13 : 9781119549802
Neuf
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